This invention relates generally to information tracking and processing and particularly to passively and automatically tracking food consumption and nutrient levels (i.e. calories, protein, sodium, etc.) based on food purchases.
Individual tracking of daily diet and exercise is a very useful part of maintaining one's health and nutritional balance. Caloric over-consumption, poor nutritional balance and lack of physical activity are known drivers of negative health outcomes, such as obesity and diabetes, in modernized nations. A common factor in both prevention and treatment of chronic illness is modifying health behavior factors such as nutrition, exercise, tobacco, and alcohol consumption. However, for many individuals, daily diet logging is tedious, and often individuals misreport the amounts and types of food they eat—leading to data that is worse than consistently and passively tracked data that is accurate and used to predict food consumption, such as purchase history.
The recently intensified interest in population health management and development of new technologies has enabled increased adoption of health behavior tracking and planning, such as digital dietary logging and activity tracking. However, existing solutions of health behavior tracking and planning do not allow users quantitatively, accurately and consistently track their dietary intake in a user friendly way and the existing solutions often require continuous active tracking activities from the users. For example, conventional self-report food frequency questionnaires are known for being imprecise. Conventional food journals are accurate only when food items are tracked at the time of consumption, but very few people typically take the time and effort to provide this level of details about what they eat, for more than a period of a couple of weeks; food journaling performs poorly in populations.